Determining Attributes for Discrete Choice Experiments in 
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Determining Attributes for Discrete Choice Experiments in Consumer Research
Determining Attributes for Discrete Choice Experiments in Consumer Research

Author(s): Pedro Longart
Subject(s): Marketing / Advertising
Published by: Transnational Press London
Keywords: Discrete Choice Experiments; Consumer Preferences; Attribute development; Conjoint Analysis, Attribute Reduction;

Summary/Abstract: Attribute development for Discrete Choice Experiments (DCEs) through qualitative research is a shallowly covered area. Particularly, research is scant in terms of detail about attribute reduction and development. First of all, the paper reviews the literature and justify DCEs as an appropriate method for determining consumer preferences, with particular focus on services. The researcher conducted a DCE on preferences for restaurants for leisure purposes. Whilst finding there was not a clear guidance, the author proposes a clear methodology for guiding DCE researchers regarding the determination of attributes in consumer research, particularly in the service industry. The case study of restaurant attribute development is used. In this context, the first stage consisted in a thorough review of the literature combined with a thematic analysis of six focus group interviews conducted in the South East of the UK. Attribute reduction took place through constant comparison analysis and the method is comprehensively explained in the paper. The study also looked for control variables and found that occasion for eating out is a very salient variable to be tested in the following DCE which consisted in an Adaptive Choice Based Conjoint online survey (Sawtooth Software). It was found the that combining literature review with focus group interviews results in richer attributes because they are based on more complex and nuanced data. Finally, a proposal with nine steps for attribute development is provided.

  • Issue Year: 10/2022
  • Issue No: 2
  • Page Range: 425-441
  • Page Count: 17
  • Language: English